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IFSI continues work with “Big Data” towards food security

Two recent events built upon the momentum from momentum from last year’s food security symposium that focused on analysis of big data to address food insecurity. These activities capitalize on the combined power of Illinois investigators working in agricultural sciences and data sciences.

Machine Learning: Farm-to-Table

A two-day event in conjunction with the Midwest Big Data Hub, “Machine Learning: Farm-to-Table Workshop,” brought together domain scientists to stimulate new data-driven research and development activity at the intersections of agriculture, bioinformatics, food-energy-water, and food security communities.

“Last year’s food security symposium caught the interest of the Midwest Big Data Hub so this event combined our forces to identify research areas and gaps for people working in the spaces of big data and agriculture. My personal quest was to see that international themes were included,” said Kathy Baylis, associate professor in agricultural and consumer economics and a member of the event’s steering committee.

Novel data analysis facilitated by machine learning, and other big data approaches have the potential to help solve difficult agricultural production, environmental and nutritional challenges, both in the United States and abroad.

“Machine learning can vastly improve predictive models, using both higher data frequency, and greater data ‘depth,’ such as a greater number and range of characteristics, than we can apply in more traditional statistical analyses,” said Baylis.

The event included attendees from other Midwestern universities and industry.

“Getting these people in the same room is helpful to see how the methods can best be applied,” said Baylis. She added that smaller groups met during the afternoons to define key research areas for moving forward and to begin working on proposal submissions.

“It is really exciting to see the extent of the appetite for facilitating access to novel methods of data collection and use in agriculture and food security,” said Baylis.

A second event during the same week, the "Data Science in Food, Energy, and Water Summit" served to unite researchers on the Illinois campus using big data in the spaces of food, energy, and water.

“This event covered a slightly broader space and served to show us specifically who is already working on what and how we can move best move forward at the University of Illinois,” said Baylis.

The summit was sponsored by the Illinois Data Science Initiative, a new collective of people at Illinois who are passionate about bringing Illinois’ tremendous research tradition and resources together with the power of data science.

Specifically the purpose of this summit was to identify:

Impactful research conducted at the University of Illinois in the intersection of Big Data, Food, Energy, and Water;

Challenges, opportunities and possible collaborations among Illinois faculty, staff, and students working in this area;

Opportunities for engagement with industry, non-government organizations, and government agencies in this area;

Potential roles for a new Institute of Data Analytics in supporting research, education, or engagement programs that facilitate the use of Big Data skills, tools, and techniques in our work.

Researchers from the College of ACES had a strong presence at the summit; its presenters included:

Members of the ACES community who are interested in participating in work on big data for food security and the environment should visit this group’s website to register to receive communications: http://idsi.illinois.edu/.